AI基础之展示

  在训练完网络后，我们需要将需要识别的图片输入模型中并输出结果，下面是具体代码。

import torch
from PIL import Image
import torchvision.transforms as trans
def testImage():
    net = torch.load("models/net.pth")
    img = Image.open("images/car.jpg")
    transform = trans.Compose([
        trans.Resize(32),
        trans.CenterCrop(32),
        trans.ToTensor(),
        trans.Normalize((0.4914, 0.4822, 0.4465),(0.2023, 0.1994, 0.2010))
    ])
    img = transform(img).unsqueeze(0)
    output = net(img.cuda())
    classes = ('plane','car', 'bird','cat','deer','dog','frog','horse','ship','truck')
    index = output.argmax(1)
    print("预测结果是：{0}".format(classes[index]))

testImage()